is one of many sections of ITS 102, the freshman seminar, each of
which is on a separate topic. The class meets once a week for 55
minutes, as is limited to a 20 student enrollement.
traditionally been largely a descriptive science, differing in many
ways from the quantitative nature of physics and engineering. However,
great advances in biology, including the successful sequencing of the
human genome, have led us to the threshold of a new approach to
biology. In this "new" biology, computer models of complex biological
systems are combined with advanced biological experiments to create an
unprecedented level of understanding. As quantitative models are
defined, we also become able to apply the principles of engineering to
design new systems. In this course we will discuss some of the key
successes that have been made in the recent past, as well as the major
challenges that are open to be solved, in fields including: protein
design and engineering, systems biology, biological computing, and
synthetic biology. We will also discuss the challenges of bridging
traditionally separate fields, and how to become effectively
Pre-requisites: The course is open
to students admitted to the ITS Undergraduate College.
The goal of this course is to introduce students
to the field of mathematical and computational biology, with an
emphasis on its interdisciplinary nature. The course aims to draw
students of mixed backgrounds (including both biology and applied
mathematics majors) and to foster interdisciplinary interactions.
Topics are drawn from a wide-range of problems in biology, including
the modeling of populations, the dynamics of signal transduction and
gene-regulatory networks, and the simulation of protein structure and
dynamics. A computer laboratory component allows students to apply
their knowledge to real-world problems.
Pre-requisites: All students taking the course should have
taken a two-semester sequence in calculus (differentiation and
integration), such as MAT 131/132 or AMS 160/161, as well as an
introductory course in molecular biology (BIO 202). Additionally,
students should have deeper background in either biology or math.
Thus, upper division standing (U3 or U4) is required. Students with
experience in both quantitative methods and biology, but lacking the
specific prerequisites, may request permission to enroll from the
Note, this course is part
of the core preparation for the Ph.D. qualifying exam in Applied Math
Review of techniques of multivariate
calculus, convergence and limits, matrix analysis, vector space
basics, and Lagrange multipliers. This course is a review of topics
in linear algebra and advanced calculus that students should have
encountered in their undergraduate studies. The methods and concepts
covered are essential for more advanced work in applied
Pre-requisites: A course in linear
algebra and in multivariate calculus.
This is a two semester course in which students
spend at least eight weeks in each of three different laboratories
actively participating in the research of participating Computational
Biology faculty. Participants will additionally attend weekly Journal
Club meetings, where they will engage in active discussion of papers
taken from the current scientific literature. Note, the laboratory
rotations are required of first year Ph.D. students from the
Computational Biology track in AMS; PhD students from other tracks in
AMS are additionally welcome on engage in rotations with participating
faculty. Masters students may sign up for the Journal Club, but do
not partake in rotations.
This class will survey many of the
key techniques used in diverse aspects of computational biology. We
will focus on how to successfully formulate a statement of the problem
to be solved, and how that formulation can guide in selecting the most
suitable computational approach. A set of problems from a diverse
range of problems in biology will be used as examples. Note:
Informatic methods for genomic analysis (such as data mining and
analysis of nucleic acid and protein sequences) will not be covered.
These topics are covered thoroughly in CSE 549.
Pre-requisites: None. Some familiarity with basic
concepts in linear algebra and calculus will be needed; extra help on
these topics will be available. See the instructor for more
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